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Table 4 Results of the performance analyses of ProMirII-g and miR-abela using human, mouse and rat genome data.

From: Filtering of false positive microRNA candidates by a clustering-based approach

Software Statistics Human Mouse (All) Mouse (Distinct) Rat
ProMirII-g # of predictions 690 656 640 615
  # of TPs 215 199 183 127
  # of FPs 475 457 457 485
  # of real miRNAs missed 25 46 29 19
  SE 89.58% 81.22% 85.92% 86.99%
  PPV 31.16% 30.34% 28.59% 20.65%
miR-abela # of predictions 1036 915 901 646
  # of TPs 149 140 126 86
  # of FPs 887 775 775 560
  # of real miRNAs missed 91 105 86 60
  SE 62.08% 57.14% 59.43% 58.90%
  PPV 14.38% 15.30% 13.98% 13.31%
  1. It should be noted that in the mouse genome, 25 of the pre-miRNAs are duplicated. In other words, only 212 mouse pre-miRNAs are distinct in the genome. To avoid overestimation of the performance of the software, we identify the duplicated ones and conduct two measurements. #, number; FP, false positives; TP, true positives; SE, sensitivity; PPV, positive predictive value.